ArticleJMIR human factors2018
How Can Social Media Lead to Co-Production (Co-Delivery) of New Services for the Elderly Population? A Qualitative Study.
Article in JMIR human factors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Public Discourse Toward Older Drivers in Japan Using Social Media Data From 2010 to 2022: Longitudinal Analysis.JMIR infodemiology · 2025Article
- From Digital Inclusion to Digital Transformation in the Prevention of Drug-Related Deaths in Scotland: Qualitative Study.Journal of medical Internet research · 2024Article
- Expectations, concerns and experiences of rehabilitation patients during the COVID-19 pandemic in Germany: a qualitative analysis of online forum posts.BMC health services research · 2021Article
- Why Health Care Professionals Belong to an Intensive Care Virtual Community: Qualitative Study.Journal of medical Internet research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe future of health care services in the European Union faces the triple challenges of aging, fiscal restriction, and inclusion. Co-production offers ways to manage informal care resources to help them cater for the growing needs of elderly people. Social media (SM) is seen as a critical enabler for co-production.
objectiveThe objective of this study was to investigate how SM-private Facebook groups, forums, Twitter, and blogging-acts as an enabler of co-production in health and care by facilitating its four underlying principles: equality, diversity, accessibility, and reciprocity.
methodsWe used normalization process theory as our theoretical framework to design this study. We conducted a qualitative study and collected data through 20 semistructured interviews and observation of the activities of 10 online groups and individuals. We then used thematic analysis and drew on principles of co-production (equality, diversity, accessibility, and reciprocity) as a deductive coding framework to analyze our findings.
resultsOur findings point to distinct patterns of feature use by different people involved in care of elderly people. This diversity makes possible the principles of co-production by offering equality among users, enabling diversity of use, making experiences accessible, and encouraging reciprocity in the sharing of knowledge and mutual support. We also identified that explication of common resources may lead to new forms of competition and conflicts. These conflicts require better management to enhance the coordination of the common pool of resources.
conclusionsSM uses afford new forms of organizing and collective engagement between patients, carers, and professionals, which leads to change in health and care communication and coordination.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.